There have been past systems which provide recommendations for content. Such recommendation systems have been available, for example, for music services. Several music services curate the best or most relevant songs catered to a user's listening habits within that music service's ecosystem. Often the playlists are curated in advance and the user “selects” a playlist by identifying a particular artist, song or genre. However, such music recommendation systems are tailored to the individual user, but fail to consider the tastes of a group of individuals that may be listening and/or viewing music content together. In the case where the music recommendation is tailored to an individual user, the recommendation is typically limited to inputs received by that particular music ecosystem. As such, there is a need to create an audio video recommendation system that will show programming that caters to the tastes of a group of individuals.